Measurements and Models of the Atmospheric Ar/N 2 ratio Mark Battle (Bowdoin College) Michael Bender (Princeton) Melissa B. Hendricks (Princeton) David T. Ho (Princeton/ Columbia) Robert Mika (Princeton) Galen McKinley (MIT/INE Mexico) Song-Miao Fan (Princeton) Tegan Blaine (Scripps) Ralph Keeling (Scripps) 2002 Fall AGU 12/09/02 Funding from: NSF NOAA GCRP Ford Res. Labs NDSEGFP
On the agenda: What makes a good tracer Why Ar/N 2 How (and where) we measure Ar/N 2 What we observe Comparison with models Conclusions and future prospects
The ideal tracer (one experimentalist’s perspective) Conservative Known sources and sinks, globally distributed Seasonally varying over land and ocean Measurable with great signal to noise
Ar/N 2 : The almost ideal tracer (one experimentalist’s perspective) Conservative Known sources and sinks, globally distributed Seasonally varying over land and ocean Measurable with great signal to noise chemically and biologically inert
Ar/N 2 : The almost ideal tracer (one experimentalist’s perspective) Conservative Known sources and sinks, globally distributed Seasonally varying over land and ocean Measurable with great signal to noise chemically and biologically inert oceanic sources driven by heat fluxes
Ar/N 2 : The almost ideal tracer (one experimentalist’s perspective) Conservative Known sources and sinks, globally distributed Seasonally varying over land and ocean Measurable with great signal to noise chemically and biologically inert oceanic sources driven by heat fluxes seasonal, but ocean only
Ar/N 2 : The almost ideal tracer (one experimentalist’s perspective) Conservative Known sources and sinks, globally distributed Seasonally varying over land and ocean Measurable with great signal to noise chemically and biologically inert oceanic sources driven by heat fluxes seasonal, but ocean only well, maybe not great…
The Ar/N 2 source/sink Atmosphere Ar: 1 O 2 : 22.5 N 2 : 84
The Ar/N 2 source/sink Atmosphere Ar: 1 O 2 : 22.5 N 2 : 84 Heat Fluxes Ar/N 2
The Ar/N 2 source/sink Atmosphere Ar: 1 O 2 : 22.5 N 2 : 84 Heat Fluxes Ar/N 2 O 2 /N 2 (thermal)
A quick word on units: Ar/N 2 changes are small Ar/N 2 per meg (Ar/N 2sa – Ar/N 2st )/(Ar/N 2st ) x per meg = per mil
Our measurement technique: Paired 2-l glass flasks IRMS (Finnigan Delta+XL) 40/28 and 32/28 Custom dual-inlet system Standards: High pressure Al cylinder For more details: Sunday afternoon poster Ho et al. GC72B-0230
Princeton Ar/N 2 cooperative flask sampling network
Climatology of Ar/N 2 seasonal cycle Monthly average values shown Multiple years (~3) stacked
Testing models with observations Observed & modeled heat fluxes Solubility equations Atmospheric transport model Predicted Ar/N 2 ECMWF or MIT OGCM (NCEP/COADS) TM2 or GCTM
Data-Model comparison Overall agreement
Data-Model comparison Overall agreement Phase problems
Syowa Transport matters
MacQuarie Heat fluxes matter
Cape Grim Transport and heat fluxes matter
Data-Model comparison Overall agreement Phase problems SYO: Transport matters MAC: Heat fluxes matter CGT: Both terms matter
Conclusions and the future… Ar/N 2 a promising “new” tracer General data-model agreement Better observations to come Need Ar/N 2 as active tracer in OGCMs Ready for Ar/N 2 in more atmospheric models
Odds and Ends Interannual variability in the seasonal cycle (perhaps primarily atmospheric) Secular trend: Tiny (~0.2 per meg/yr) Size of O 2 /N 2 thermal cycle: 13-34% of total Intersite gradients: A problem
Uncertainties All fitting techniques equivalent Std error on monthly avg. shown in plots Std error reflects: –Limited IRMS precision ( 4.0) –Fractionation during transfer from flask to IRMS ( 8.6) –Uncorrelated fractionation of flasks during collection ( 2.6) –Correlated fractionation of flasks during collection (?) –Real variability within month (?)
Correlated variability in Ar/N 2 and O 2 /N 2
Improving collection protocols
SST relaxation term in MIT OGCM